A Guidance method for robustness surrogate assisted multi-objective evolutionary algorithms

Multi-objective evolutionary algorithms for a preventive healthcare facility network design

Preventive healthcare aims at reducing the likelihood and severity of potentially life-threatening illnesses by protection and early detection. In this paper, a bi-objective mathematical model is proposed to design a network of preventive healthcare facilities so as to minimize total travel and waiting time as well as establishment and staffing cost. Moreover, each facility acts as M/M/1 queuin...

Multi-Objective Evolutionary Guidance for Swarms

A novel approach for generating optimal flight paths for a swarm of missiles using an on-line, noise-aware, multi-objective evolutionary algorithm is introduced. The trajectory shape is controlled by flying via intermediate points which are adjusted dynamically by the evolutionary algorithm, then towards the point of impact with the target.

Multi-Objective Evolutionary Algorithms

Evolutionary Multi-Objective Algorithms

The versatility that genetic algorithm (GA) has proved to have for solving different problems, has make it the first choice of researchers to deal with new challenges. Currently, GAs are the most well known evolutionary algorithms, because their intuitive principle of operation and their relatively simple implementation; besides they have the ability to reflect the philosophy of evolutionary co...

Multi-Objective Evolutionary Algorithms

Real world optimization problems are often too complex to be solved through analytical means. Evolutionary algorithms, a class of algorithms that borrow paradigms from nature, are particularly well suited to address such problems. These algorithms are stochastic methods of optimization that have become immensely popular recently, because they are derivative-free methods, are not as prone to get...